SBIR/STTR Research Award
RARE CELL ANALYSIS BY MULTI-SPECTRAL FLOW IMAGING
Award amount
$124,380Program and phase
SBIR · Phase IAward year
2002Award details
- Awarding agency
- Department of Health and Human Services
- Branch
- National Institutes of Health
- Recipient company
- Amnis Corporation
- Proposal award date
- Not reported
- Contract end date
- Not reported
- UEI
- Not reported
- Solicitation number
- Not reported
- Topic code
- Not reported
Research abstract
The ability to detect and analyze rare malignant cells in body fluids has profound implications for the early detection of malignancy as well as for monitoring of residual disease and metastases. Current methodologies for accurately detecting abnormal cells within a population of normal cells are limited. Amnis' ImageStream technology combines the high-resolution imaging performance of microscopy and the high-speed cellular analysis and sorting capabilities of flow cytometry in a single platform. ImageStream employs time delay integration detection, resulting in up to a 1000 fold increase in signal collection over conventional instrument designs. The goal of this Phase I study is to optimize algorithms, electronics, and assays for the detection and analysis of rare exfoliated cells in body fluids. The image segmentation algorithm will be redesigned to operate with brightfield imagery as well as fluorescence and implemented on high-speed image computing hardware. A morphological feature set will be developed to discriminate epithelial cells. Ultimately, it is expected that instrumentation based on ImageStream technology will find application in the biological research laboratory, drug discovery arena, and in the clinical setting as a screening system for he early detection of cancer. PROPOSED COMMERCIAL APPLICATIONS: Amnis' ImageStream technology represents an entirely new class of cellular analysis instrumentation with numerous opportunities for commercialization. It is expected that ImageStream will find application in drug discovery, biological research, genomics and proteomics, non- invasive prenatal diagnostics and early-stage cancer detection.
Technology keywords
Not reported